Rail tracks are currently manually inspected i.e. either by involving people who have to walk along the rail track to visually identify a problem or by watching live or delayed video images from one or more cameras mounted on a platform that moves on the rail track. In the latter case, the inspection is based on visual inspection of “moving” video (or by examining many “still” small frames from the video) captured as the cameras move over the rails. Such methods and systems are not only slow and tedious, but also lower the chance and speed of detecting foreign objects or abnormalities around rail track due to human input required, and the associated risk of human error. Such methods are also resource intensive.